241 related articles for article (PubMed ID: 37256875)
1. Ensemble learning-based radiomics with multi-sequence magnetic resonance imaging for benign and malignant soft tissue tumor differentiation.
Lee S; Lee SY; Jung JY; Nam Y; Jeon HJ; Jung CK; Shin SH; Chung YG
PLoS One; 2023; 18(5):e0286417. PubMed ID: 37256875
[TBL] [Abstract][Full Text] [Related]
2. Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions.
Zhang Q; Peng Y; Liu W; Bai J; Zheng J; Yang X; Zhou L
J Magn Reson Imaging; 2020 Aug; 52(2):596-607. PubMed ID: 32061014
[TBL] [Abstract][Full Text] [Related]
3. Radiomics of diffusion-weighted MRI compared to conventional measurement of apparent diffusion-coefficient for differentiation between benign and malignant soft tissue tumors.
Lee SE; Jung JY; Nam Y; Lee SY; Park H; Shin SH; Chung YG; Jung CK
Sci Rep; 2021 Jul; 11(1):15276. PubMed ID: 34315971
[TBL] [Abstract][Full Text] [Related]
4. Natural Changes in Radiological and Radiomics Features on MRIs of Soft-Tissue Sarcomas Naïve of Treatment: Correlations With Histology and Patients' Outcomes.
Fadli D; Kind M; Michot A; Le Loarer F; Crombé A
J Magn Reson Imaging; 2022 Jul; 56(1):77-96. PubMed ID: 34939705
[TBL] [Abstract][Full Text] [Related]
5. [Value of radiomics models based on MRI diffusion weighted imaging and apparent diffusion coefficient in differentiating benign and malignant thyroid nodules].
Xu HJ; Yang Q; He P; Luo HH; Deng WM; Liu Z; Luo DH
Zhonghua Yi Xue Za Zhi; 2023 Nov; 103(41):3279-3286. PubMed ID: 37926572
[No Abstract] [Full Text] [Related]
6. Performance of Machine Learning Methods Based on Multi-Sequence Textural Parameters Using Magnetic Resonance Imaging and Clinical Information to Differentiate Malignant and Benign Soft Tissue Tumors.
Nakagawa M; Nakaura T; Yoshida N; Azuma M; Uetani H; Nagayama Y; Kidoh M; Miyamoto T; Yamashita Y; Hirai T
Acad Radiol; 2023 Jan; 30(1):83-92. PubMed ID: 35725692
[TBL] [Abstract][Full Text] [Related]
7. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
Wang X; Wan Q; Chen H; Li Y; Li X
Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
[TBL] [Abstract][Full Text] [Related]
8. Diagnostic performance of diffusion-weighted (DWI) and dynamic contrast-enhanced (DCE) MRI for the differentiation of benign from malignant soft-tissue tumors.
Choi YJ; Lee IS; Song YS; Kim JI; Choi KU; Song JW
J Magn Reson Imaging; 2019 Sep; 50(3):798-809. PubMed ID: 30663160
[TBL] [Abstract][Full Text] [Related]
9. A Magnetic Resonance Imaging Radiomics Signature to Distinguish Benign From Malignant Orbital Lesions.
Duron L; Heraud A; Charbonneau F; Zmuda M; Savatovsky J; Fournier L; Lecler A
Invest Radiol; 2021 Mar; 56(3):173-180. PubMed ID: 32932375
[TBL] [Abstract][Full Text] [Related]
10. Prostate Cancer Differentiation and Aggressiveness: Assessment With a Radiomic-Based Model vs. PI-RADS v2.
Chen T; Li M; Gu Y; Zhang Y; Yang S; Wei C; Wu J; Li X; Zhao W; Shen J
J Magn Reson Imaging; 2019 Mar; 49(3):875-884. PubMed ID: 30230108
[TBL] [Abstract][Full Text] [Related]
11. Bi-parametric magnetic resonance imaging based radiomics for the identification of benign and malignant prostate lesions: cross-vendor validation.
Ji X; Zhang J; Shi W; He D; Bao J; Wei X; Huang Y; Liu Y; Chen JC; Gao X; Tang Y; Xia W
Phys Eng Sci Med; 2021 Sep; 44(3):745-754. PubMed ID: 34075559
[TBL] [Abstract][Full Text] [Related]
12. Whole-tumor 3D volumetric MRI-based radiomics approach for distinguishing between benign and malignant soft tissue tumors.
Fields BKK; Demirjian NL; Hwang DH; Varghese BA; Cen SY; Lei X; Desai B; Duddalwar V; Matcuk GR
Eur Radiol; 2021 Nov; 31(11):8522-8535. PubMed ID: 33893534
[TBL] [Abstract][Full Text] [Related]
13. Preoperative MRI-Based Radiomic Machine-Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft-Tissue Lesions: A Two-Center Study.
Wang H; Zhang J; Bao S; Liu J; Hou F; Huang Y; Chen H; Duan S; Hao D; Liu J
J Magn Reson Imaging; 2020 Sep; 52(3):873-882. PubMed ID: 32112598
[TBL] [Abstract][Full Text] [Related]
14. Magnetic resonance radiomic feature performance in pulmonary nodule classification and impact of segmentation variability on radiomics.
Koo CW; Kline TL; Yoon JH; Vercnocke AJ; Johnson MP; Suman G; Lu A; Larson NB
Br J Radiol; 2022 Dec; 95(1140):20220230. PubMed ID: 36367095
[TBL] [Abstract][Full Text] [Related]
15. An Integrated Radiomics Model Incorporating Diffusion-Weighted Imaging and
Zhang L; Yao R; Gao J; Tan D; Yang X; Wen M; Wang J; Xie X; Liao R; Tang Y; Chen S; Li Y
Front Oncol; 2021; 11():732704. PubMed ID: 34527594
[TBL] [Abstract][Full Text] [Related]
16. [Application of MRI-based Radiomics Models in the Assessment of Hepatic Metastasis of Rectal Cancer].
Hu SX; Yang K; Wang XR; Wen DG; Xia CC; Li X; Li ZL
Sichuan Da Xue Xue Bao Yi Xue Ban; 2021 Mar; 52(2):311-318. PubMed ID: 33829708
[TBL] [Abstract][Full Text] [Related]
17. Prediction of High-Risk Cytogenetic Status in Multiple Myeloma Based on Magnetic Resonance Imaging: Utility of Radiomics and Comparison of Machine Learning Methods.
Liu J; Zeng P; Guo W; Wang C; Geng Y; Lang N; Yuan H
J Magn Reson Imaging; 2021 Oct; 54(4):1303-1311. PubMed ID: 33979466
[TBL] [Abstract][Full Text] [Related]
18. Development and external validation of a multiparametric MRI-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer: a retrospective multicenter study.
Li Z; Zhang J; Zhong Q; Feng Z; Shi Y; Xu L; Zhang R; Yu F; Lv B; Yang T; Huang C; Cui F; Chen F
Eur Radiol; 2023 Mar; 33(3):1835-1843. PubMed ID: 36282309
[TBL] [Abstract][Full Text] [Related]
19. MRI-Based Computer-Aided Diagnostic Model to Predict Tumor Grading and Clinical Outcomes in Patients With Soft Tissue Sarcoma.
Yang Y; Zhou Y; Zhou C; Zhang X; Ma X
J Magn Reson Imaging; 2022 Dec; 56(6):1733-1745. PubMed ID: 35303756
[TBL] [Abstract][Full Text] [Related]
20. Relevance of apparent diffusion coefficient features for a radiomics-based prediction of response to induction chemotherapy in sinonasal cancer.
Bologna M; Calareso G; Resteghini C; Sdao S; Montin E; Corino V; Mainardi L; Licitra L; Bossi P
NMR Biomed; 2022 Apr; 35(4):e4265. PubMed ID: 32009265
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]